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 "name": "Scale limits",
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 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0000-0003-0757-275X"
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   "@id": "https://wulfkaal.github.io/claims/3782217-023",
   "identifier": "kaal:claim:3782217-023",
   "text": "The most obvious harm from news consolidation is that national and international centralized corporations do not devote the same degree of focus to the interests of the local communities they serve, because love does not scale.",
   "abstract": "The most obvious problem with news consolidation is that national or interna- tional centralized corporations do not devote the same degree of focus to the inter- ests of the local communities they serve.",
   "citation": "Craig Calcaterra, Wulf A. Kaal, The Importance of History In Decentralization (2021). SSRN: https://ssrn.com/abstract=3782217",
   "datePublished": "2021",
   "claim_type": "failure",
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   "scope_conditions": [
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4755632-002",
   "identifier": "kaal:claim:4755632-002",
   "text": "Transformer neural network architecture removes the scale constraint on training data but not the quality constraint, so data quality continues to be a major unsolved issue for large language models even where internet scale corpora are available.",
   "abstract": "data quality continues to be a huge issue for LLMs",
   "citation": "Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632",
   "datePublished": "2024",
   "claim_type": "failure",
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